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Relevant bibliographies by topics / KNOWLEDGE SYSTEMS

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Academic literature on the topic 'KNOWLEDGE SYSTEMS'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 January 2023

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Journal articles on the topic "KNOWLEDGE SYSTEMS"

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Šilerová, E., and L. Kučírková. "Knowledge and information systems." Agricultural Economics (Zemědělská ekonomika) 54, No. 5 (June 13, 2008): 217–23. http://dx.doi.org/10.17221/245-agricecon.

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We can see that the today’s management level of informations is not quite fully controlled in most businesses. Nowadays generation of information systems creates support for business processes with the aim of optimalization of these processes on the bases of experiences with similar business processes. Today’s information systems are at the level of data management or information management. Quite a few manage information processes in the area of tactical and strategic planning and almost no one manages processes in the areas of gathering, distribution and sharing of knowledge in business. We can say, that investments to the information technologies do not guarantee the successful way to the management of information and knowledge in business.

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Damasio, Antonio R., and Daniel Tranel. "Knowledge systems." Current Biology 2, no. 4 (April 1992): 198. http://dx.doi.org/10.1016/0960-9822(92)90527-h.

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Damasio, Antonio R., and Daniel Trane. "Knowledge systems." Current Opinion in Neurobiology 2, no. 2 (April 1992): 186–90. http://dx.doi.org/10.1016/0959-4388(92)90010-i.

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Parasuraman. D, Parasuraman D. "Emerging Perspectives of Knowledge Management Systems." International Journal of Scientific Research 3, no. 7 (June 1, 2012): 282–84. http://dx.doi.org/10.15373/22778179/july2014/90.

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Johnson, N. E. "Knowledge based systems series Vol. 1: Knowledge acquisition for knowledge based systems Vol. 2: Knowledge acquisition tools for expert systems." Knowledge-Based Systems 3, no. 3 (September 1990): 181. http://dx.doi.org/10.1016/0950-7051(91)90030-6.

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Henderson, T., E. Weitz, C. Hansen, and A. Mitiche. "Multisensor Knowledge Systems." International Journal of Robotics Research 7, no. 6 (December 1988): 114–33. http://dx.doi.org/10.1177/027836498800700609.

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Galup, Stuart D., Ronald Dattero, and Richard C. Heeks. "Knowledge Management Systems." Information Resources Management Journal 15, no. 1 (January 2002): 22–27. http://dx.doi.org/10.4018/irmj.2002010103.

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Buchanan, Bruce G., Daniel Bobrow, Randall Davis, John McDermott, and Edward H. Shortliffe. "Knowledge-Based Systems." Annual Review of Computer Science 4, no. 1 (June 1990): 395–416. http://dx.doi.org/10.1146/annurev.cs.04.060190.002143.

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Kahn, M. G. "Knowledge-Based Systems." Yearbook of Medical Informatics 02, no. 01 (August 1993): 399–401. http://dx.doi.org/10.1055/s-0038-1637984.

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Priha, I. "Integrated knowledge systems." Artificial Intelligence in Engineering 4, no. 2 (April 1989): 70–78. http://dx.doi.org/10.1016/0954-1810(89)90002-2.

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Dissertations / Theses on the topic "KNOWLEDGE SYSTEMS"

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Windisch, Markus. "Cyber Knowledge Systems." Fraunhofer-Institut für Verfahrenstechnik und Verpackung IVV, 2018. https://slub.qucosa.de/id/qucosa%3A32447.

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Prudnik, D. O. "Knowledge management systems." Thesis, Київський національний університет технологій та дизайну, 2018. https://er.knutd.edu.ua/handle/123456789/10771.

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Schlobach, Klaus Stefan. "Knowledge discovery in hybrid knowledge representation systems." Thesis, King's College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272023.

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Patelli, Alina. "Knowledge-centric autonomic systems." Thesis, Aston University, 2017. http://publications.aston.ac.uk/37574/.

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Autonomic computing revolutionised the commonplace understanding of proactiveness in the digital world by introducing self-managing systems. Built on top of IBM’s structural and functional recommendations for implementing intelligent control, autonomic systems are meant to pursue high level goals, while adequately responding to changes in the environment, with a minimum amount of human intervention. One of the lead challenges related to implementing this type of behaviour in practical situations stems from the way autonomic systems manage their inner representation of the world. Specifically, all the components involved in the control loop have shared access to the system’s knowledge, which, for a seamless cooperation, needs to be kept consistent at all times. A possible solution lies with another popular technology of the 21st century, the Semantic Web,and the knowledge representation media it fosters, ontologies. These formal yet flexible descriptions of the problem domain are equipped with reasoners, inference tools that, among other functions, check knowledge consistency. The immediate application of reasoners in an autonomic context is to ensure that all components share and operate on a logically correct and coherent “view” of the world. At the same time, ontology change management is a difficult task to complete with semantic technologies alone, especially if little to no human supervision is available. This invites the idea of delegating change management to an autonomic manager, as the intelligent control loop it implements is engineered specifically for that purpose. Despite the inherent compatibility between autonomic computing and semantic technologies,their integration is non-trivial and insufficiently investigated in the literature. This gap represents the main motivation for this thesis. Moreover, existing attempts at provisioning autonomic architectures with semantic engines represent bespoke solutions for specific problems (load balancing in autonomic networking, deconflicting high level policies, informing the process of correlating diverse enterprise data are just a few examples). The main drawback of these efforts is that they only provide limited scope for reuse and cross-domain analysis (design guidelines, useful architectural models that would scale well across different applications and modular components that could be integrated in other systems seem to be poorly represented). This work proposes KAS (Knowledge-centric Autonomic System), a hybrid architecture combining semantic tools such as: • an ontology to capture domain knowledge,• a reasoner to maintain domain knowledge consistent as well as infer new knowledge, • a semantic querying engine,• a tool for semantic annotation analysis with a customised autonomic control loop featuring: • a novel algorithm for extracting knowledge authored by the domain expert, • “software sensors” to monitor user requests and environment changes, • a new algorithm for analysing the monitored changes, matching them against known patterns and producing plans for taking the necessary actions, • “software effectors” to implement the planned changes and modify the ontology accordingly. The purpose of KAS is to act as a blueprint for the implementation of autonomic systems harvesting semantic power to improve self-management. To this end, two KAS instances were built and deployed in two different problem domains, namely self-adaptive document rendering and autonomic decision-support for career management. The former case study is intended as a desktop application, whereas the latter is a large scale, web-based system built to capture and manage knowledge sourced by an entire (relevant) community. The two problems are representative for their own application classes –namely desktop tools required to respond in real time and, respectively, online decision support platforms expected to process large volumes of data undergoing continuous transformation – therefore, they were selected to demonstrate the cross-domain applicability (that state of the art approaches tend to lack) of the proposed architecture. Moreover, analysing KAS behaviour in these two applications enabled the distillation of design guidelines and of lessons learnt from practical implementation experience while building on and adapting state of the art tools and methodologies from both fields. KAS is described and analysed from design through to implementation. The design is evaluated using ATAM (Architecture Trade off Analysis Method) whereas the performance of the two practical realisations is measured both globally as well as deconstructed in an attempt to isolate the impact of each autonomic and semantic component. This last type of evaluation employs state of the art metrics for each of the two domains. The experimental findings show that both instances of the proposed hybrid architecture successfully meet the prescribed high-level goals and that the semantic components have a positive influence on the system’s autonomic behaviour.

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Munro, David. "Knowledge-sharing on knowledge management systems : the role of organisational and system support /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18588.pdf.

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Trimble, John. "Knowledge acquisition and the system dynamics methodology." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/23337.

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Lakkaraju, Sai Kiran. "Synchronising subjective knowledge and knowledge management systems in organisations." View thesis, 2008. http://handle.uws.edu.au:8081/1959.7/31670.

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Thesis (Ph.D.)--University of Western Sydney, 2008.
"A thesis submitted to the University of Western Sydney, College of Health and Science, School of Computing and Mathematics in fulfilment of the requirements for the degree of Doctor of Philosophy." Includes bibliography.

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Aikenhead, Michael. "Legal knowledge-based systems : new directions in system design." Thesis, Durham University, 2001. http://etheses.dur.ac.uk/4384/.

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This thesis examines and critiques the concept of 'legal knowledge-based’ systems. Work on legal knowledge-based systems is dominated by work in 'artificial intelligence and law’. It seeks to automate the application of law and to automate the solution of legal problems. Automation however, has proved elusive. In contrast to such automation, this thesis proposes the creation of legal knowledge-based systems based on the concept of augmentation of legal work. Focusing on systems that augment legal work opens new possibilities for system creation and use. To inform how systems might augment legal work, this thesis examines philosophy, psychology and legal theory for information they provide on how processes of legal reasoning operate. It is argued that, in contrast to conceptions of law adopted in artificial intelligence and law, 'sensemaking' provides a useful perspective with which to create systems. It is argued that visualisation, and particularly diagrams, are an important and under considered element of reasoning and that producing systems that support diagramming of processes of legal reasoning would provide useful support for legal work. This thesis reviews techniques for diagramming aspects of sensemaking. In particular this thesis examines standard methods for diagramming arguments and methods for diagramming reasoning. These techniques are applied in the diagramming of legal judgments. A review is conducted of systems that have been constructed to support the construction of diagrams of argument and reasoning. Drawing upon these examinations, this thesis highlights the necessity of appropriate representations for supporting reasoning. The literature examining diagramming for reasoning support provides little discussion of appropriate representations. This thesis examines theories of representation for insight they can provide into the design of appropriate representations. It is concluded that while the theories of representation that are examined do not determine what amounts to a good representation, guidelines for the design and choice of representations can be distilled. These guidelines cannot map the class of legal knowledge-based systems that augment legal sensemaking, they can however, be used to explore this class and to inform construction of systems.

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Lagos, Nikolaos. "Knowledge-based product support systems." Thesis, Cardiff University, 2007. http://orca.cf.ac.uk/54573/.

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This research helps bridge the gap between conventional product support, where the support system is considered as a stand-alone application, and the new paradigm of responsive one, where the support system frequently communicates with its environment and reacts to stimuli. This new paradigm would enable product support knowledge to be captured, stored, processed, and updated automatically, being delivered to the users when, where and in the form they need it. The research reported in this thesis first defines Product Support Systems (PRSSs) as electronic means that provide accurate and up-to-date information to the user in a coherent and personalised manner. Product support knowledge is then identified as the integration of product, task, user, and support documentation knowledge. Next, the thesis focuses on an ontology-based model of the structure, relations, and attributes of product support knowledge. In that model product support virtual documentation (PSVD) is presented as an aggregation of Information Objects (IOs) and Information Object Clusters (IOCs). The description of PSVD is followed by an analysis of the relation between IOs, IOCs, and domain knowledge. Then, the thesis builds on the ontology-based representation of product support knowledge and explores the synergy between product support, problem solving, and knowledge engineering. As a result, a structured problem solving approach is introduced that combines case-based adaptation and model-based generation techniques. Based on that approach a knowledge engineering framework for product support systems is developed. A conceptual model of context-aware product support systems that extends the framework is then introduced. The conceptual model includes an ontology-based representation of knowledge related to the users, their activities, the support environment, and the device being used. An approach to semi-automatically integrating design and documentation data is also proposed as part of context-aware product support systems development process.

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Yoon, Changwoo. "Domain-specific knowledge-based informational retrieval model using knowledge reduction." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0011560.

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Books on the topic "KNOWLEDGE SYSTEMS"

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Debenham, John K. Knowledge systems design. New York: Prentice Hall, 1990.

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Debenham, John K. Knowledge systems design. New York: Prentice Hall, 1989.

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Maier, Ronald. Knowledge Management Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24779-1.

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Maier, Ronald. Knowledge Management Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04380-6.

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Priti, Sajja, ed. Knowledge-based systems. Sudbury, Mass: Jones and Bartlett, 2010.

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R, Gaines Brian, and Boose John H, eds. Knowledge acquisition for knowledge-based systems. London: Academic Press, 1988.

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Aussenac, N., G. Boy, B. Gaines, M. Linster, J. G. Ganascia, and Y. Kodratoff, eds. Knowledge Acquisition for Knowledge-Based Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57253-8.

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Designing knowledge-based systems. Englewood Cliffs, N.J: Prentice-Hall, 1986.

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Designing knowledge-based systems. London: Kogan Page, 1985.

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Brulé, James F. Knowledge acquisition. New York: McGraw-Hill, 1989.

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Book chapters on the topic "KNOWLEDGE SYSTEMS"

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Klir, George J. "Systems Knowledge." In Facets of Systems Science, 123–34. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1331-5_7.

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Micouin, Patrice. "Knowledge Systems." In Model-Based Systems Engineering, 41–58. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118579435.ch3.

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Klir, George J. "Systems Knowledge." In Facets of Systems Science, 101–11. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-0718-9_7.

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Turnbull, David. "Knowledge Systems: Local Knowledge." In Encyclopaedia of the History of Science, Technology, and Medicine in Non-Western Cultures, 2495–501. Dordrecht: Springer Netherlands, 2016. http://dx.doi.org/10.1007/978-94-007-7747-7_8705.

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Shute, Valerie J. "My Knowledge of Knowledge." In Intelligent Tutoring Systems, 4. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-68716-5_4.

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Doignon, Jean-Paul, and Jean-Claude Falmagne. "Surmise Systems." In Knowledge Spaces, 62–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-58625-5_4.

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Wang, Zhongtuo, and Jiangning Wu. "Knowledge Systems Engineering: A Complex System View." In Knowledge Synthesis, 107–49. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-55218-5_7.

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Koskinen, Kaj U., and Rainer Breite. "Systems." In Uninterrupted Knowledge Creation, 5–12. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57303-4_2.

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Swain, Martin. "Knowledge." In Encyclopedia of Systems Biology, 1072–73. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1030.

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Nakamori, Yoshiteru. "Knowledge Management." In Translational Systems Sciences, 63–91. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9887-2_4.

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Conference papers on the topic "KNOWLEDGE SYSTEMS"

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White, Stephanie M. "Application of cognitive theories and knowledge management to requirements engineering." In 2010 4th Annual IEEE Systems Conference. IEEE, 2010. http://dx.doi.org/10.1109/systems.2010.5482489.

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Henderson, Thomas C. "Multisensor Knowledge Systems." In 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, edited by Charles B. Weaver. SPIE, 1988. http://dx.doi.org/10.1117/12.946669.

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Sainter, P., K. Oldham, A. Larkin, A. Murton, and R. Brimble. "Product Knowledge Management Within Knowledge-Based Engineering Systems." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/dac-14501.

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Abstract Knowledge-based engineering systems are now becoming more commonplace in engineering industry. There is a need to ensure the technology is used correctly and to provide the user with all the possible benefits that the system can offer. This paper looks at how product knowledge can be managed within knowledge-based engineering systems to ensure that the knowledge retains its value and usefulness during the product lifecycle. Presently, the use of these systems has been for the short-term benefit of the company. However, it is believed that it is important to consider longer-term issues also, since knowledge normally has a half-life of around 20 years. The main aim of this paper is to demonstrate the need for product knowledge management within knowledge-based engineering systems by looking at key issues that are related to the longer-term use of these systems. This paper will also provide a product knowledge management scheme for the development and management of product knowledge within knowledge-based engineering systems, thereby extending the benefits of knowledge-based engineering systems into the longer-term.

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Simmons, D., N. Ellis, and J. Stanley. "Knowledge sharing between distributed knowledge based systems." In Eleventh Annual International Phoenix Conference on Computers and Communication [1992 Conference Proceedings]. IEEE, 1992. http://dx.doi.org/10.1109/pccc.1992.200509.

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Liu, Zhao, and Yixin Chen. "Positioning Appropriate Knowledge in Knowledge-based Systems." In the 2019 International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3335550.3335554.

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KREBS, SCOTT, and PRASHANT BORDIA. "PREDICTING KNOWLEDGE SHARING ON KNOWLEDGE MANAGEMENT SYSTEMS." In Proceedings of the First iKMS International Conference on Knowledge Management. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702081_0015.

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Kelemen, Jozef. "From knowledge workers to knowledge managing systems: An exercise in transferring experience with knowledge-based systems into knowledge management." In 2009 International Conference on Intelligent Engineering Systems (INES). IEEE, 2009. http://dx.doi.org/10.1109/ines.2009.4924757.

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Benbya, Hind, and Marshall W. Van Alstyne. "Eliciting and Validating Knowledge in Knowledge Management Systems." In 2008 41st Annual Hawaii International Conference on System Sciences. IEEE, 2008. http://dx.doi.org/10.1109/hicss.2008.142.

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Karna, Nyoman, Iping Supriana, and Nur Maulidevi. "Knowledge sharing between similar domain knowledge management systems." In THE 2016 CONFERENCE ON FUNDAMENTAL AND APPLIED SCIENCE FOR ADVANCED TECHNOLOGY (CONFAST 2016): Proceeding of ConFAST 2016 Conference Series: International Conference on Physics and Applied Physics Research (ICPR 2016), International Conference on Industrial Biology (ICIBio 2016), and International Conference on Information System and Applied Mathematics (ICIAMath 2016). Author(s), 2016. http://dx.doi.org/10.1063/1.4953988.

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Achten, Henri, J. Dijkstra, R. Oxman, and Thijs Bax. "Knowledge-Based Systems Programming for Knowledge Intensive Teaching." In eCAADe 1995: Multimedia and Architectural Disciplines. eCAADe, 1995. http://dx.doi.org/10.52842/conf.ecaade.1995.139.

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Reports on the topic "KNOWLEDGE SYSTEMS"

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Chandrasekaran, B. Distributed Knowledge-Based Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1989. http://dx.doi.org/10.21236/ada211984.

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Feigenbaum, Edward A., Robert S. Engelmore, and Paul C. Rosenbloom. Knowledge-Based Systems Research. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada277505.

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Feigenbaum, Edward A., Robert S. Engelmore, and Paul C. Rosenbloom. Knowledge-Based Systems Research. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada225816.

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Hertz, Jana C., Derick W. Brinkerhoff, Robin Bush, and Petrarca Karetji. Knowledge Systems: Evidence to Policy Concepts in Practice. RTI Press, June 2020. http://dx.doi.org/10.3768/rtipress.2020.pb.0024.2006.

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This policy brief reviews the evolution of knowledge-to-policy studies and the emergence of systems perspectives. We explore the less well understood issue of how to grow and reinforce knowledge systems in settings where they are weak and underdeveloped. We offer a knowledge systems model that encapsulates current thinking and present an example of an effort to strengthen a knowledge system, drawn from a project managed by RTI in Indonesia. We conclude with some recommendations for strengthening knowledge systems including promoting debate among a diversity of voices within the knowledge system, providing sustained stakeholder commitment to the systems approach, investing in the components of the knowledge system as well as the interaction between components, fostering a balance between government mechanisms and space for civil society perspectives, and exploring how knowledge systems can engage the private sector. We conclude with suggestions for applying the knowledge systems model in new country contexts including use of a political economy analysis as well as gauging readiness of government actors, research institutes, and media to engage.

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Pasquale, Joseph. Knowledge-Based Distributed Systems Management. Fort Belvoir, VA: Defense Technical Information Center, June 1986. http://dx.doi.org/10.21236/ada619313.

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Stengel, Robert F. Knowledge-Based Systems for Computational Control. Fort Belvoir, VA: Defense Technical Information Center, November 1992. http://dx.doi.org/10.21236/ada260409.

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Minker, Jack. Deductive Databases and Knowledge Base Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1995. http://dx.doi.org/10.21236/ada295498.

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Lunt, Teresa F., and Thomas D. Garvey. Multilevel Security for Knowledge Based Systems. Fort Belvoir, VA: Defense Technical Information Center, December 1990. http://dx.doi.org/10.21236/ada234974.

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Cuginia, John V. Programming languages for knowledge-based systems. Gaithersburg, MD: National Bureau of Standards, 1987. http://dx.doi.org/10.6028/nbs.sp.500-145.

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Zamora, Antonio. 41. DISCOVERY, SEARCH, AND COMMUNICATION OF TEXTUAL KNOWLEDGE RESOURCES IN DISTRIBUTED SYSTEMS a. Discovering and Utilizing Knowledge Sources for Metasearch Knowledge Systems. Office of Scientific and Technical Information (OSTI), March 2008. http://dx.doi.org/10.2172/946818.

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